• DocumentCode
    130058
  • Title

    Fault estimation for LPV system with LFT parameter dependence

  • Author

    Hanbin Wang ; Huamin Chen ; Zhengxin Weng

  • Author_Institution
    Dept. of Autom., Shanghai Jiao Tong Univ., Shanghai, China
  • fYear
    2014
  • fDate
    28-30 July 2014
  • Firstpage
    560
  • Lastpage
    565
  • Abstract
    The robust H-infinity fault estimation problem for a class of Linear Parameter Varying (LPV) systems which can be formulated in an LFT framework has been studied in this paper. Based on small gain techniques, a new method for the design of a robust gain scheduled H-infinity fault estimator is developed, the resulting estimator achieves high performance by incorporating the available measurements of the time-varying parameters, and therefore adjusts to the current plant dynamics. The existence of such gain-scheduled H-infinity fault estimator is characterized in terms of linear matrix inequalities. The underlying synthesis problem is a convex program for which efficient optimization techniques are available. To demonstrate the proposed method, a numerical example is considered. Simulation results show that the designed LPV fault estimator is effective for a class of LPV plants.
  • Keywords
    H optimisation; convex programming; linear matrix inequalities; linear systems; LFT framework; LFT parameter dependence; LPV fault estimator; LPV plants; LPV system; convex program; linear matrix inequalities; linear parameter varying systems; plant dynamics; robust H-infinity fault estimation problem; robust gain scheduled H-infinity fault estimator; time-varying parameters; Automation; Estimation; H infinity control; Linear matrix inequalities; Null space; Robustness; Vectors; LFT; Linear Parameter Varying system; fault estimation; robust H-infinity filtering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Automation (ICIA), 2014 IEEE International Conference on
  • Conference_Location
    Hailar
  • Type

    conf

  • DOI
    10.1109/ICInfA.2014.6932717
  • Filename
    6932717